Complete Genome Sequence of an Escherichia coli Strain Isolated from Laboratory Mouse Stool for Use as a Chassis for Transgene Delivery to the Murine Microbiome.

Tools to explore functional changes in the microbiome are limited. Here, we report the complete genome sequence of a strain of Escherichia coli that was isolated from murine stool. This sequence will provide essential information to further develop this tool, and similar tools, to explore the complex murine microbiome.

Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors.

CRISPR interference (CRISPRi) enables programmable, reversible, and titratable repression of gene expression (knockdown) in mammalian cells. Initial CRISPRi-mediated genetic screens have showcased the potential to address basic questions in cell biology, genetics, and biotechnology, but wider deployment of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and challenges in generating cell models with consistent CRISPRi-mediated knockdown. Here, we present next-generation CRISPRi sgRNA libraries and effector expression constructs that enable strong and consistent knockdown across mammalian cell models. First, we combine empirical sgRNA selection with a dual-sgRNA library design to generate an ultra-compact (1-3 elements per gene), highly active CRISPRi sgRNA library. Next, we compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides an excellent balance between strong on-target knockdown and minimal non-specific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines with stable expression of Zim3-dCas9 and robust on-target knockdown. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.

Intestinal transgene delivery with native E. coli chassis allows persistent physiological changes.

Live bacterial therapeutics (LBTs) could reverse diseases by engrafting in the gut and providing persistent beneficial functions in the host. However, attempts to functionally manipulate the gut microbiome of conventionally raised (CR) hosts have been unsuccessful because engineered microbial organisms (i.e., chassis) have difficulty in colonizing the hostile luminal environment. In this proof-of-concept study, we use native bacteria as chassis for transgene delivery to impact CR host physiology. Native Escherichia coli bacteria isolated from the stool cultures of CR mice were modified to express functional genes. The reintroduction of these strains induces perpetual engraftment in the intestine. In addition, engineered native E. coli can induce functional changes that affect physiology of and reverse pathology in CR hosts months after administration. Thus, using native bacteria as chassis to "knock in" specific functions allows mechanistic studies of specific microbial activities in the microbiome of CR hosts and enables LBT with curative intent.

Intermittent Hypoxia and Hypercapnia Alter Diurnal Rhythms of Luminal Gut Microbiome and Metabolome.

Obstructive sleep apnea (OSA), characterized by intermittent hypoxia and hypercapnia (IHC), affects the composition of the gut microbiome and metabolome. The gut microbiome has diurnal oscillations that play a crucial role in regulating circadian and overall metabolic homeostasis. Thus, we hypothesized that IHC adversely alters the gut luminal dynamics of key microbial families and metabolites. The objective of this study was to determine the diurnal dynamics of the fecal microbiome and metabolome of Apoe-/- mice after a week of IHC exposure. Individually housed, 10-week-old Apoe-/- mice on an atherogenic diet were split into two groups. One group was exposed to daily IHC conditions for 10 h (Zeitgeber time 2 [ZT2] to ZT12), while the other was maintained in room air. Six days after the initiation of the IHC conditions, fecal samples were collected every 4 h for 24 h (6 time points). We performed 16S rRNA gene amplicon sequencing and untargeted liquid chromatography-mass spectrometry (LC-MS) to assess changes in the microbiome and metabolome. IHC induced global changes in the cyclical dynamics of the gut microbiome and metabolome. Ruminococcaceae, Lachnospiraceae, S24-7, and Verrucomicrobiaceae had the greatest shifts in their diurnal oscillations. In the metabolome, bile acids, glycerolipids (phosphocholines and phosphoethanolamines), and acylcarnitines were greatly affected. Multi-omic analysis of these results demonstrated that Ruminococcaceae and tauro-ß-muricholic acid (TßMCA) cooccur and are associated with IHC conditions and that Coriobacteriaceae and chenodeoxycholic acid (CDCA) cooccur and are associated with control conditions. IHC significantly change the diurnal dynamics of the fecal microbiome and metabolome, increasing members and metabolites that are proinflammatory and proatherogenic while decreasing protective ones. IMPORTANCE People with obstructive sleep apnea are at a higher risk of high blood pressure, type 2 diabetes, cardiac arrhythmias, stroke, and sudden cardiac death. We wanted to understand whether the gut microbiome changes induced by obstructive sleep apnea could potentially explain some of these medical problems. By collecting stool from a mouse model of this disease at multiple time points during the day, we studied how obstructive sleep apnea changed the day-night patterns of microbes and metabolites of the gut. Since the oscillations of the gut microbiome play a crucial role in regulating metabolism, changes in these oscillations can explain why these patients can develop so many metabolic problems. We found changes in microbial families and metabolites that regulate many metabolic pathways contributing to the increased risk for heart disease seen in patients with obstructive sleep apnea.

Human Skin, Oral, and Gut Microbiomes Predict Chronological Age.

Human gut microbiomes are known to change with age, yet the relative value of human microbiomes across the body as predictors of age, and prediction robustness across populations is unknown. In this study, we tested the ability of the oral, gut, and skin (hand and forehead) microbiomes to predict age in adults using random forest regression on data combined from multiple publicly available studies, evaluating the models in each cohort individually. Intriguingly, the skin microbiome provides the best prediction of age (mean ± standard deviation, 3.8 ± 0.45 years, versus 4.5 ± 0.14 years for the oral microbiome and 11.5 ± 0.12 years for the gut microbiome). This also agrees with forensic studies showing that the skin microbiome predicts postmortem interval better than microbiomes from other body sites. Age prediction models constructed from the hand microbiome generalized to the forehead and vice versa, across cohorts, and results from the gut microbiome generalized across multiple cohorts (United States, United Kingdom, and China). Interestingly, taxa enriched in young individuals (18 to 30 years) tend to be more abundant and more prevalent than taxa enriched in elderly individuals (>60 yrs), suggesting a model in which physiological aging occurs concomitantly with the loss of key taxa over a lifetime, enabling potential microbiome-targeted therapeutic strategies to prevent aging.IMPORTANCE Considerable evidence suggests that the gut microbiome changes with age or even accelerates aging in adults. Whether the age-related changes in the gut microbiome are more or less prominent than those for other body sites and whether predictions can be made about a person's age from a microbiome sample remain unknown. We therefore combined several large studies from different countries to determine which body site's microbiome could most accurately predict age. We found that the skin was the best, on average yielding predictions within 4 years of chronological age. This study sets the stage for future research on the role of the microbiome in accelerating or decelerating the aging process and in the susceptibility for age-related diseases.

Effect of Obesogenic Medications on Weight-Loss Outcomes in a Behavioral Weight-Management Program.

OBJECTIVE: This study aimed to evaluate a possible association between the use of obesogenic medications and inadequate weight loss in a behavioral weight-management program. METHODS: This is a case-control, single-center study of 666 adult patients within a Veterans Health Administration health system who participated in the MOVE! behavioral weight-loss program. The cohort was divided into responders (n = 150), patients who achieved ≥ 5% total weight loss by the end of the MOVE! program, and nonresponders (n = 516), those who achieved < 5% total weight loss. We reviewed each patient's medical records for exposure to obesogenic medication during the time of treatment. RESULTS: Approximately 62% (n = 411) of patients entering MOVE! had a prescription for obesogenic medications. Obesogenic medication use was associated with worse weight-loss outcomes, and participants were 37% less likely to achieve a clinically meaningful (≥ 5% total weight loss) outcome at the end of the MOVE! program (odds ratio, 0.633; 95% CI: 0.427-0.937; adjusted P = 0.022). Patients who received three or more medications (n = 72) had the greatest difficulty achieving 5% weight loss compared with the control group (odds ratio, 0.265; 95% CI: 0.108-0.646; adjusted P = 0.003). CONCLUSIONS: The use of provider-prescribed obesogenic medications was associated with worse weight-loss outcomes in a behavioral weight-loss program. Closer scrutiny of patient medications is necessary to help improve outcomes of weight-loss treatments.